Liu Liu

Robust Imitation Learning from Corrupted Demonstrations

2022 · arXiv (Cornell University)

We consider offline Imitation Learning from corrupted demonstrations where a constant fraction of data can be noise or even arbitrary outliers. Classical approaches such as Behavior Cloning assumes that demonstrations are collected by an presumably …

Dual-branch Density Ratio Estimation for Signed Network Embedding

2022 · Proceedings of the ACM Web Conference 2022

Signed network embedding (SNE) has received considerable attention in recent years. A mainstream idea of SNE is to learn node representations by estimating the ratio of sampling densities. Though achieving promising performance, these methods based …

On-Orbit Health Management of Thermal Control Subsystem of a Micro Satellite

2022 · 2022 Global Reliability and Prognostics and Health Management (PHM-Yantai)

As a subsystem of spacecraft, thermal control plays a basic role in guarantee. According to the reliability requirements of a micro satellite, a thermal on-orbit health management system is proposed, which has ensured the normal …

Stochastic Optimization for Nonconvex Problem With Inexact Hessian Matrix, Gradient, and Function

2023 · IEEE Transactions on Neural Networks and Learning Systems

Trust region (TR) and adaptive regularization using cubics (ARC) have proven to have some very appealing theoretical properties for nonconvex optimization by concurrently computing function value, gradient, and Hessian matrix to obtain the next search …

Towards Alleviating Text-to-Image Retrieval Hallucination for CLIP in Zero-shot Learning

2024 · arXiv (Cornell University)

Pretrained cross-modal models, for instance, the most representative CLIP, have recently led to a boom in using pre-trained models for cross-modal zero-shot tasks, considering the generalization properties. However, we analytically discover that CLIP suffers from …